An Integrated Analytics Environment. Designed for analytsts.
RTECH INSIGHT CLOUD FEATURES
An analyst-first approach to Big Data analytics.
Enabling business users to obtain value from Big Data with minimal IT involvement is the key design principle behind the Rtech Insight Cloud.
For Big Data to reach its full potential in an organization, it must be exposed to the substantial number of business analysts who primarily work with SQL and visual analytics tools. But in most organizations, Hadoop data is off limits to them, and any requests for access are routed through IT.
The Rtech Insight Cloud is composed of analyst-friendly tools that aid with tasks across the analytics lifecycle. No IT intervention or command-line know-how is required for analysts to bring data into the environment, create and publish aggregates, and query data in the Hadoop data lake. Analysts have direct access to data in Hadoop and are completely self-sufficient in this environment.
Comprehensive Analytics Support
The Rtech Insight Cloud provides a combination of powerful built-in capabilities and integrations with standard analytic tools to meet a wide range of analytics requirements.
Analysts use Rtech’s feature-rich, collaborative query interface to execute queries, explore data, and share queries with other analysts. This intuitive yet capable web interface provides a central location for analysts’ query-based analyses. It allows analysts to query both aggregated and detailed data, as well as define and schedule aggregates, on their own from a single interface.
Streaming and Batch Igestion
Rtech offers native data ingestion capabilities to assist users with the critical steps of loading data into the analytics environment and validating data prior to analysis.
Rtech provides a web-based data ingestion portal that allows analysts to bring data into Hadoop easily, using both streaming and batch modes of data ingestion. From this portal, analysts can specify data sources, curate data, and set up data pipelines to process incoming data. Entire pipelines can be specified and scheduled in the graphical interface without any need to write code. This data ingestion feature is well-suited to handling large-scale, high-velocity event streams.
Fastest Time to Insight
Get a Big Data analytics environment instantly, with no customer setup required.
The Rtech Insight Cloud is a complete end-to-end architecture with integrated ingestion, transformation, and query application capabilities from a single provider. As a cloud-based solution, it can be made available immediately with all components integrated and functional, compared to alternatives where you have to piece together various components, possibly including hardware, yourself.
Performance and Reliability
Rtech’s ability to deliver Big Data performance and reliability is unparalleled.
Performance begins with Rtech’s purpose-built Big Data infrastructure—designed and optimized for Hadoop and Spark—which underlies the analytics layers above. The Rtech Insight Cloud supports multiple SQL engines that provide the interactive query performance analysts are accustomed to with MPP databases. For more performance-sensitive applications, Rtech can be configured for high-speed ingestion and real-time dashboards.
As mission-critical analytics is moved onto the Hadoop data lake, system reliability becomes a key requirement. Rtech is the only provider that operates your Big Data analytics infrastructure for you. The Rtech Insight Cloud has an always-on SLA, so you can be assured of the reliability of your analysts’ environment.
The Rtech Insight Cloud features a converged architecture, so a separate analytic data store, such as Redshift or Vertica, is not needed.
The elimination of the analytic store, commonly used for aggregated data, reduces the cost and management burden on your organization. With the Rtech Insight Cloud, you do not have to license and administer a separate data store. In addition, you avoid the complexity of maintaining aggregates in a separate location and minimize data movement.
The Rtech Insight Cloud also allows easier scalability to petabyte-scale. The relational databases typically used as analytic data stores do not scale effectively beyond tens of terabytes, while a Hadoop-based system offers high scalability.